spaCy vs TextAnalyzer
spaCy
spacy.ioTextAnalyzer
textanalyzer.orgSide by side
| Figure | spaCy | TextAnalyzer |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 1 | 1 |
| Spec score · Text Analytics Software | 8.4 (#4) | 7.1 (#27) |
| Founded | 2015 | 2020 |
| Maker | Explosion identifies itself as the maker of spaCy and describes itself as a software company specializing in developer tools and services for AI and natural language processing. | The resource is provided by Jonah Berger, Garrick Sherman, and Lyle Ungar of the University of Pennsylvania. |
| Purpose | spaCy is a Python library for advanced natural language processing, designed for production use and processing large volumes of text. | TextAnalyzer provides NLP tools for researchers to analyze text data. |
| Support | The site links to GitHub Discussions, an issue tracker and Stack Overflow for community help. | Comments, suggestions, and bug reports can be sent to [email protected]. |
Plans
In their own words
spaCy
spaCy is a free, open-source Python library for building natural language processing applications, with a focus on production use and large volumes of text. Its components handle named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphology, and entity linking. The project lists support for 75+ languages and 84 trained pipelines for 25 languages, though trained pipelines are not available for every language. Developers can configure and train custom pipelines, describe training runs with configuration files, and package pipelines for installation as Python packages. spaCy can use pretrained transformers through spacy-transformers, and supports custom models in PyTorch, TensorFlow, and other frameworks. spaCy Projects supports workflows for downloads, commands, checksum verification, and caching, along with integrations for tracking, demos, model serving, distributed training, and Hugging Face Hub. Installation is available through pip, conda, or source on Linux, macOS, and Windows. The library can run on a user's servers without data leaving them. It is not a hosted software-as-a-service product or web application. The library is free under AGPL or a commercial license; transformer models require a GPU to run effectively.
TextAnalyzer
TextAnalyzer has no write-up on Specifiction yet; its figures are above.